Adding organization card and overview of the fine-tuned models

README.md

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 title: README
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+emoji: 📊
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+short_description: Organization card providing details on the fine-tuned models
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-Edit this `README.md` markdown file to author your organization card.
+![SNSF Logo](https://data.snf.ch/img/logo_snf_white_en.svg)
+
+Based on a government mandate, the Swiss National Science Foundation (SNSF) supports scientific research in all academic disciplines.
+It is the leading organisation for the promotion of scientific research in Switzerland.
+On the [Data Portal](https://data.snf.ch/), the SNSF publishes data on the evaluated projects and the persons involved in order to provide transparency and facilitate the analysis of funding activities.
+
+In this space, the SNSF Data Team provides fine-tuned models for classifying grant peer review texts along 12 categories relevant to the evaluation criteria specified by the SNSF.
+In particular, the models are based on the `allenai/specter2_base` model and fine-tuned for a binary classification task on a sentence level.
+For more details, see the the following preprint:
+
+**A Supervised Machine Learning Approach for Assessing Grant Peer Review Reports**
+
+by [Gabriel Okasa](https://orcid.org/0000-0002-3573-7227),
+[Alberto de León](https://orcid.org/0009-0002-0401-2618),
+[Michaela Strinzel](https://orcid.org/0000-0003-3181-0623),
+[Anne Jorstad](https://orcid.org/0000-0002-6438-1979),
+[Katrin Milzow](https://orcid.org/0009-0002-8959-2534),
+[Matthias Egger](https://orcid.org/0000-0001-7462-5132), and
+[Stefan Müller](https://orcid.org/0000-0002-6315-4125), available on arXiv: https://arxiv.org/abs/2411.16662 .
+
+The fine-tuned models are listed below together with the description of the respective classification category:
+
+- `snsf-data/specter2-review-track-record`: *Does the sentence address the scientific qualifications of the applicant(s)/team?*
+- `snsf-data/specter2-review-relevance-originality-topicality`: *Does the sentence address the scientific relevance/impact/originality of the proposed research project?*
+- `snsf-data/specter2-review-suitability`: *Does the sentence address the suitability of the methods to be used within the proposed research project?*
+- `snsf-data/specter2-review-feasibility`: *Does the sentence address the feasibility of the proposed research project?*
+- `snsf-data/specter2-review-applicant`: *Does the sentence address the applicant(s)/team or their qualifications, without mentioning quantitative indicators?*
+- `snsf-data/specter2-review-applicant-quantity`: *Does the sentence use quantitative indicators to describe the applicant(s)or team?*
+- `snsf-data/specter2-review-proposal`: *Does the sentence address the proposal or specific parts of it, as opposed to the applicant(s) or context beyond the proposal (such as the research field or the funding scheme’s objectives etc.)?*
+- `snsf-data/specter2-review-method`: *Does the sentence address the methods to be used in the proposed research project?*
+- `snsf-data/specter2-review-positive`: *Is the sentence itself a positive statement or does it contain a positive statement?*
+- `snsf-data/specter2-review-negative`: *Is the sentence itself a negative statement or does it contain a negative statement?*
+- `snsf-data/specter2-review-suggestion`: *Does the sentence suggest how to improve the proposal?*
+- `snsf-data/specter2-review-rationale`: *Does the sentence provide rationale supporting the positive or negative statement?*
+
+The model cards provide further details on the fine-tuning procedure and evaluation metrics as well as minimal examples for usage of the models.